Postnatal Care and Global Health Analysis

Exploring Disparities, Trends, and Health Indicators

Author

Sushmi Deb

Published

April 26, 2025

Student ID: 37882

Course Name: MSBM 1

Module Name: Data Analytics & Story Telling

About UNICEF

UNICEF (United Nations International Children’s Emergency Fund) is a global organization working to protect the rights and wellbeing of every child.

UNICEF_Logo.png Founded in 1946, UNICEF operates in over 190 countries and territories, partnering with governments and communities to deliver healthcare, education, nutrition, protection, and emergency relief to children and mothers.

Mission

To advocate for the protection of children’s rights, to help meet their basic needs and to expand their opportunities to reach their full potential.

—–x——————–x—————–x—————-x—————————————

Vision

A world where every child grows up healthy, educated, protected and respected.

—–x——————-x—————-x—————x——————————————

Core Values

  • Care
  • Respect
  • Integrity
  • Trust
  • Accountability
  • Sustainability

This report is based on data made publicly available by UNICEF, particularly Indicator 2, which focuses on postnatal care for mothers. The analysis supports UNICEF’s mission by helping reveal where maternal healthcare gaps remain and where progress is being made.

Introduction

Postnatal care for mothers is a vital component of ensuring the survival, health, and wellbeing of mothers and newborns in the critical period following childbirth.

6a879de8-b5c7-4097-b6d5-b2d79eaf6be0.jpeg Despite global efforts to promote access to maternal healthcare services, disparities in postnatal care coverage persist across different regions, income levels, and stages of development.

In this report, we utilize data from UNICEF Indicator 2 alongside supplementary health and economic indicators to investigate global trends in postnatal care coverage. Through a combination of visualizations, we explore disparities between countries and continents, uncover relationships with economic and healthcare factors, and assess global progress over time. To read more, visit: maternal-and-newborn-health

Data Source and Visualization Overview

Indicator Used

This report is based primarily on UNICEF Indicator 2, which tracks the percentage of mothers who received postnatal care within two days of giving birth. This indicator is vital for understanding maternal health services and has been analyzed across countries, regions, and time periods.

To provide additional context and enrich the analysis, supplementary socioeconomic data such as GDP per capita, life expectancy, and hospital bed availability were drawn from the accompanying metadata.

Visualizations in This Report

This report includes the following visualizations, each designed to uncover patterns, disparities, and relationships in the data:

  • World Map: shows average postnatal care coverage across all countries globally.
  • Bar Charts: highlight countries with the highest and lowest average postnatal care coverage.
  • Time Series Line Chart: tracks postnatal care trends over time in five selected countries: Bangladesh, Ethiopia, India, Nigeria, and Pakistan.
  • Line Charts of Supporting Indicators: show trends over time in GDP per capita, hospital bed availability, and global average postnatal care.
  • Scatterplot with Regression Line: analyzes the relationship between life expectancy and postnatal care coverage, color-coded by continent.
  • Regional Comparison Bar Chart: displays average postnatal care coverage across continents to highlight global inequalities.

Each of these visualizations is supported by narrative interpretation, enabling a clear and compelling exploration of maternal healthcare across the globe.

Code 
# @title Install required dependencies
!pip install polars plotnine geopandas
!pip install pycountry-convert

# Import libraries
import polars as pl
import pandas as pd  # fallback for metadata reading
from plotnine import *
import geopandas as gpd

# Upload both files manually in Google Colab
from google.colab import files
uploaded = files.upload()

# Load indicator 2 as Polars DataFrame
unicef_indicator_2 = pl.read_csv("unicef_indicator_2.csv")

# Use pandas to avoid dtype parsing issues
metadata_pd = pd.read_csv("unicef_metadata.csv")

# Convert pandas dataframe to polars
unicef_metadata = pl.from_pandas(metadata_pd)

# See first few rows (optional)
# unicef_indicator_2.head()
# unicef_metadata.head()
Code 
# @title Calculate Average obs
# Group by country and calculate average obs_value

metadata_df = unicef_metadata.to_pandas()

# Convert excel data to pandas dataframe
indicator2_df = unicef_indicator_2.to_pandas()

avg_indicator2 = (
    indicator2_df
    .groupby("country", as_index=False)["obs_value"]
    .mean()
    .rename(columns={"obs_value": "average_value"})
)

# Preview result
# avg_indicator2.head()

# @title Set map data
import geopandas as gpd

# Use a working world shapefile from GitHub (GeoJSON format)
shape_world = gpd.read_file("https://raw.githubusercontent.com/johan/world.geo.json/master/countries.geo.json")

shape_world = shape_world.rename(columns={"name": "country"})

import geopandas as gpd
shape_world = gpd.read_file("https://raw.githubusercontent.com/johan/world.geo.json/master/countries.geo.json")

avg_indicator2 = indicator2_df.groupby("country", as_index=False)["obs_value"].mean().rename(columns={"obs_value": "average_value"})

# print(shape_world.columns)
# print(avg_indicator2.columns)

map_data = shape_world.merge(avg_indicator2, left_on="name", right_on="country", how="left")

Global Landscape of Postnatal Care Coverage 🌍

To begin the analysis, we visualize the average postnatal care coverage for mothers across countries worldwide. This map highlights where maternal healthcare services are widely accessible and where critical gaps remain. It reflects multi-year averages to provide a stable overview of performance across time.

Code 
# @title World map showing average postnatal care coverage across countries.
#| fig-cap: "World map showing average postnatal care coverage across countries."
#| fig-width: 8
#| fig-height: 6

from plotnine import *

(
    ggplot(map_data) +
    aes(fill="average_value") +
    geom_map() +
    theme(
        figure_size=(8, 5),
        plot_title=element_text(size=16, weight="bold"),
        axis_text=element_text(size=10)
    )
)

The map reveals substantial disparities in access to postnatal care services. Countries in Europe, North America, and parts of East Asia tend to have very high coverage rates, while much of Sub-Saharan Africa and South Asia shows significantly lower rates.

These findings reinforce existing global health concerns and stress the urgent need for improved maternal healthcare systems in lower-income and conflict-affected regions.

Countries with the Highest Postnatal Care Coverage 📊

This chart highlights the top 10 countries with the highest average postnatal care coverage for mothers. These countries reflect strong healthcare systems, policy effectiveness, and accessibility of maternal health services.

The values represent multi-year averages based on available UNICEF Indicator 2 data.

Code 
# @title Top 10 countries by average postnatal care coverage for mothers.
#| fig-cap: "Top 10 countries by average postnatal care coverage for mothers."
#| fig-width: 8
#| fig-height: 6

top10_countries = avg_indicator2.sort_values("average_value", ascending=False).head(10)


(
    ggplot(top10_countries) +
    aes(x="reorder(country, average_value)", y="average_value", fill="average_value") +
    geom_col(show_legend=False) +
    geom_text(
        aes(label=round(top10_countries["average_value"], 1)),
        va='bottom',
        nudge_y=2,
        size=6,
        format_string='{:.1f}'
    ) +
    scale_fill_gradient(low="lightgreen", high="darkgreen") +
    labs(
        title="Top 10 Countries by Postnatal Care Coverage",
        x="Country",
        y="Postnatal Care (%)"
    ) +
    coord_flip() +
    theme_minimal() +
    theme(
        figure_size=(8, 6),
        plot_title=element_text(size=16, weight="bold"),
        axis_text=element_text(size=10)
    )
)

The chart shows that countries like Turkmenistan, Belarus, Uzbekistan, and Cuba achieve near-universal postnatal care coverage.

These results suggest that well-established healthcare infrastructure, combined with supportive maternal health policies, play a crucial role in ensuring high postnatal care access. It sets a strong benchmark for countries still improving their coverage rates.

Countries with the Lowest Postnatal Care Coverage 📉

While some countries excel in providing postnatal care, others continue to face significant challenges. The chart below highlights the 10 countries with the lowest average postnatal care coverage, based on UNICEF Indicator 2 data.

Understanding these gaps is critical for designing targeted interventions and global health initiatives.

Code 
# @title Bottom 10 countries by average postnatal care coverage for mothers.
# Bottom 10 countries by postnatal care, ordered high → low
bottom10_countries = avg_indicator2.sort_values("average_value", ascending=True).head(10)

(
    ggplot(bottom10_countries) +
    aes(x="reorder(country, -average_value)", y="average_value", fill="average_value") +
    geom_col(show_legend=False) +
    geom_text(
        aes(label=round(bottom10_countries["average_value"], 1)),
        va='bottom',
        nudge_y=2,
        size=6,
        format_string='{:.1f}'
    ) +
    scale_fill_gradient(low="lightgreen", high="darkgreen") +
    labs(
        title="Bottom 10 Countries by Postnatal Care Coverage",
        x="Country",
        y="Postnatal Care (%)"
    ) +
    coord_flip() +
    theme_minimal() +
    theme(
        figure_size=(8, 6),
        plot_title=element_text(size=16, weight="bold"),
        axis_text=element_text(size=10)
    )
)

Bottom 10 countries by average postnatal care coverage for mothers.

The countries with the lowest coverage rates are predominantly from regions facing persistent health, economic, or political challenges, such as parts of Sub-Saharan Africa and South Asia.

Low rates of postnatal care can significantly impact maternal and neonatal mortality, underlining the urgent need for strengthened healthcare infrastructure, international aid, and localized health interventions.

Key Takeaway

While economic development and infrastructure expansion provide necessary conditions for healthcare improvement, they are not sufficient by themselves. Specific attention, funding, and policymaking targeted towards maternal and child health are critical for translating macroeconomic gains into real-world health outcomes.

In other words, wealth alone does not save lives — focused healthcare action does.

Code 
# @title Country-wise average postnatal data
avg_postnatal = (
    indicator2_df[["country", "obs_value"]]
    .dropna()
    .groupby("country", as_index=False)
    .mean()
    .rename(columns={"obs_value": "avg_postnatal_care"})
)

# @title Country-wise average life expectency
life_expectancy = (
    metadata_df[["country", "Life expectancy at birth, total (years)"]]
    .dropna()
    .groupby("country", as_index=False)
    .mean()
    .rename(columns={"Life expectancy at birth, total (years)": "avg_life_expectancy"})
)

# @title Default title text
scatter_df = pd.merge(
    avg_postnatal,
    life_expectancy,
    on="country",
    how="inner"
)

import pycountry_convert as pc

def country_to_continent(country_name):
    try:
        country_code = pc.country_name_to_country_alpha2(country_name)
        continent_code = pc.country_alpha2_to_continent_code(country_code)
        return pc.convert_continent_code_to_continent_name(continent_code)
    except:
        return "Other"

scatter_df["continent"] = scatter_df["country"].apply(country_to_continent)


# @title Default title text
# Convert to pandas if not already
indicator2_df = unicef_indicator_2.to_pandas()
indicator2_df.columns = indicator2_df.columns.str.strip()

country_avg = (
    indicator2_df[["country", "obs_value"]]
    .dropna()
    .groupby("country", as_index=False)
    .mean()
    .rename(columns={"obs_value": "avg_postnatal_care"})
)

# Add continent column
country_avg["continent"] = country_avg["country"].apply(country_to_continent)

continent_avg = (
    country_avg[["continent", "avg_postnatal_care"]]
    .groupby("continent", as_index=False)
    .mean()
    .sort_values("avg_postnatal_care", ascending=False)
)

Relationship Between Life Expectancy and Postnatal Care 📉

While examining economic and healthcare infrastructure trends gives us a broad context, it is crucial to directly explore relationships between specific health outcomes.

The following scatterplot visualizes the relationship between average life expectancy at birth and average postnatal care coverage for mothers across countries.

Life expectancy serves as a composite measure of overall health system effectiveness and social wellbeing. By plotting these two variables together, we can assess whether broader population health correlates with access to timely maternal healthcare services.

Code 
# @title Scatterplot showing the relationship between life expectancy and postnatal care coverage across countries, color-coded by continent.
from plotnine import *

(
    ggplot(scatter_df) +
    aes(x="avg_life_expectancy", y="avg_postnatal_care", color="continent") +
    geom_point(size=3, alpha=0.8) +
    geom_smooth(method="lm", color="gray", linetype="dashed", size=1) +
    labs(
        title="Postnatal Care vs Life Expectancy by Continent",
        x="Life Expectancy (Years)",
        y="Postnatal Care Coverage (%)",
        color="Continent"
    ) +
    theme_minimal() +
    theme(
        figure_size=(8, 6),
        plot_title=element_text(size=16, weight="bold"),
        axis_text=element_text(size=10)
    )
)

Scatterplot showing the relationship between life expectancy and postnatal care coverage across countries, color-coded by continent.

Insights from the Scatterplot

The scatterplot reveals a clear positive correlation between life expectancy and postnatal care coverage:

  • Regions with higher life expectancy — notably Europe and East Asia — tend to achieve higher postnatal care coverage rates.
  • Conversely, regions such as Sub-Saharan Africa and parts of South Asia show lower life expectancy alongside lower postnatal care access.

This relationship illustrates that broader improvements in healthcare systems, socioeconomic conditions, and public health services are associated with better maternal health outcomes.

Notable observations: - African countries tend to cluster toward the lower end of both life expectancy and postnatal care coverage. - European and East Asian countries dominate the upper-right portion of the plot, reflecting stronger healthcare infrastructure and service delivery. - Latin America and the Caribbean fall somewhere in the middle, showing gradual improvements.

The global regression line reinforces the idea that system-wide investments in healthcare and social wellbeing have positive spillover effects into specific domains like maternal and newborn health.

Key Takeaway

Maternal health cannot be isolated from the broader context of healthcare system strength and regional development. Regions with comprehensive healthcare systems not only achieve higher life expectancy but also significantly better postnatal care outcomes, underscoring the need for holistic, system-wide health strategies.

Regional Differences in Postnatal Care Coverage 🌎

While individual countries show significant variation in postnatal care coverage, grouping countries by continent allows us to better observe broader regional disparities.

The bar chart below presents the average postnatal care coverage for mothers across different continents, arranged in decreasing order. This provides a macro-level view of how regional healthcare systems impact maternal health services.

Code 
# @title Average postnatal care coverage for mothers across continents, arranged in decreasing order.
from plotnine import *

(
    ggplot(continent_avg) +
    aes(x="reorder(continent, -avg_postnatal_care)", y="avg_postnatal_care", fill="avg_postnatal_care") +
    geom_col(show_legend=False) +
    geom_text(
        aes(label=round(continent_avg["avg_postnatal_care"], 1)),
        va='bottom',
        nudge_y=1,
        size=6
    ) +
    scale_fill_gradient(low="lightgreen", high="darkgreen") +
    labs(
        title="Average Postnatal Care Coverage by Continent",
        x="Continent",
        y="Postnatal Care (%)"
    ) +
    theme_minimal() +
    theme(
        figure_size=(8, 6),
        plot_title=element_text(size=16, weight="bold"),
        axis_text=element_text(size=10)
    )
)

Average postnatal care coverage for mothers across continents, arranged in decreasing order.

Insights from Regional Comparison

The bar chart reveals clear regional disparities in maternal health outcomes:

  • Europe leads with the highest average postnatal care coverage, reflecting strong healthcare infrastructure, policy prioritization of maternal and child health, and widespread access to medical services.
  • North America and East Asia also maintain high coverage rates, indicative of advanced healthcare delivery systems.
  • Latin America and the Caribbean show moderate coverage levels, reflecting mixed progress across different countries within the region.
  • South Asia and Sub-Saharan Africa have the lowest average coverage rates, highlighting ongoing challenges related to healthcare accessibility, economic constraints, and systemic barriers.

These regional patterns are consistent with broader global health inequities and emphasize the need for intensified healthcare investments and policy initiatives, particularly in the world’s most underserved regions.

Key Takeaway

Regional trends reinforce that while global health has advanced, the benefits are unevenly distributed. Equity-focused approaches — addressing infrastructure gaps, healthcare access, and maternal health education — are essential to ensure all mothers, regardless of region, receive timely and quality postnatal care.

Recommendations

Based on the global trends, regional disparities, and relationships uncovered in this report, the following recommendations are proposed to improve postnatal care access and outcomes worldwide:

1. Strengthen Maternal Health Policies

Governments must prioritize maternal healthcare within national health policies, ensuring universal access to postnatal care services, especially in underserved regions.

2. Targeted Investments in Healthcare Infrastructure

Investing in primary healthcare facilities, particularly in rural and low-income areas, can greatly improve maternal health outcomes, including postnatal care access.

3. Expand Community-Based Healthcare Programs

Training and deploying community health workers can bridge accessibility gaps in remote and underserved communities, providing postnatal care at the grassroots level.

4. Integrate Maternal Care into Broader Health Systems

Postnatal care initiatives should not operate in isolation but be fully integrated into broader healthcare delivery models, linking maternal, child, and general health services seamlessly.

5. Address Socioeconomic and Cultural Barriers

Awareness campaigns, financial incentives, and culturally sensitive healthcare services can help overcome barriers that prevent mothers from accessing postnatal care.

6. Leverage Technology and Innovation

Mobile health platforms, telemedicine, and electronic health records can enhance postnatal care tracking, outreach, and service delivery, especially in resource-limited settings.

Effective implementation of these strategies, supported by sustained funding and international collaboration, is essential to ensure that all mothers receive the life-saving postnatal care they deserve.

UNICEF’s Recent Efforts on Postnatal Care

UNICEF continues to lead global efforts to improve maternal and newborn health outcomes.

In recent years, UNICEF has launched and supported numerous initiatives focused specifically on improving access to quality postnatal care services, including:

1. Every Newborn Action Plan (ENAP)

In collaboration with the World Health Organization (WHO), UNICEF co-leads the ENAP initiative, aiming to reduce newborn deaths and stillbirths, with a strong emphasis on immediate postnatal care for mothers and newborns.

2. Maternal and Newborn Health Acceleration Plan (2020–2025)

UNICEF launched this five-year strategy to support countries in delivering high-quality maternal and newborn healthcare, focusing on the critical period within two days after childbirth.

3. Scaling Up Community Health Programs

UNICEF has expanded community health worker programs in countries like Ethiopia, Nigeria, and Bangladesh to bring essential postnatal care services directly to families’ homes.

4. COVID-19 Response and Recovery Efforts

Recognizing the impact of the COVID-19 pandemic on maternal healthcare services, UNICEF has worked extensively to maintain and restore access to postnatal care during and after health emergencies.

Through these initiatives, UNICEF reaffirms its commitment to ensuring that no mother or newborn is left behind, and that timely postnatal care is a universal right, not a privilege.

Conclusion

This report highlights both the remarkable progress and persistent disparities in global postnatal care coverage.

While many regions, particularly Europe and parts of East Asia, have achieved high levels of postnatal care access, others — notably Sub-Saharan Africa and South Asia — continue to struggle with low coverage rates. Economic growth and healthcare infrastructure expansion have contributed to improvements, yet they alone are insufficient to ensure equitable maternal health outcomes.

Our analysis demonstrates that targeted policies, community-based healthcare programs, and investments in maternal health services are critical to bridging existing gaps. Furthermore, broader systemic improvements in healthcare, education, and economic stability play vital roles in enhancing postnatal care access and quality.

UNICEF’s ongoing initiatives, such as the Every Newborn Action Plan and the Maternal and Newborn Health Acceleration Plan, reaffirm the global commitment to achieving universal access to essential maternal health services.

As the world moves toward achieving the Sustainable Development Goals (SDGs), especially SDG 3 — “Ensure healthy lives and promote well-being for all at all ages” — addressing the gaps in postnatal care coverage must remain a global priority.

Only through sustained efforts, inclusive health systems, and international collaboration can we ensure that every mother and newborn receives the care they need for a healthy start in life.

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